We conduct experiments on public benchmarks for transferable recommender evaluation, including both cross-domain and cross-platform scenarios. Five domains from Amazon review datasets [1]} are used for pre-training (Food, Home, CDs, Kindle, and Movies). Then the pre-trained model will be transferred to five downstream cross-domain datasets (Scientific, Pantry, Instruments, Arts, and Office, all from Amazon) and one cross-platform dataset (Online Retailhttps://www.kaggle.com/carrie1/ecommerce-data, a UK-based online retail platform).
